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Based on the hourly observational data during 2007-2016 from surface meteorological stations in China, this paper compares the influence of 3-hourly precipitation data, mainly from the Chinese Reanalysis-Interim (CRA-Interim), ECMWF Reanalysis 5 (ERA5) and Japanese Reanalysis-55 (JRA-55), on the simulation of the spatial and temporal distribution of regional precipitation in China and the bias distribution of the simulation. The results show that: (1) The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual average precipitation in China. The simulation of topographic forced precipitation in complex terrain by using CRA-interim is more detailed, while CRA-interim has larger negative bias in central and East China, and larger positive bias in southwest China. (2) In terms of seasonal precipitation, the three sets of reanalysis datasets overestimate the precipitation in the heavy rainfall zone in spring and summer, especially in southwest China. According to CRA-interim, location of the rain belt in the First Rainy Season in South China is west by south, and the summer precipitation has positive bias in southwest and South China. (3) All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of drought and flood, but overall the CRA-Interim generally shows negative bias, while the ERA5 and JRA-55 exhibit positive bias. (4) For the diurnal variation of precipitation in summer, all the reanalysis datasets perform better in simulating the daytime precipitation than in the night, and the bias of CRA-interim is less in the Southeast and Northeast than elsewhere. (5) The ERA5 generally performs the best on the evaluation of quantitative precipitation forecast, the JRA-55 is the next, followed by the CRA-Interim. The CRA-Interim has higher missing rate and lower threat score for heavy rains; however, at the level of downpour, the CRA-Interim performs slightly better. [ABSTRACT FROM AUTHOR]

Objective To investigate the association between ambient air pollution and hospital emergency admissions in Beijing. Methods In this study, a semi-parametric generalized additive model (GAM) was used to evaluate the specific influences of air pollutants (PM 10 , SO 2 , and NO 2 ) on hospital emergency admissions with different lag structures from 2009 to 2011, the sex and age specific influences of air pollution and the modifying effect of seasons on air pollution to analyze the possible interaction. Results It was found that a 10 μg/m 3 increase in concentration of PM 10 at lag 03 day, SO 2 and NO 2 at lag 0 day were associated with an increase of 0.88%, 0.76%, and 1.82% respectively in overall emergency admissions. A 10 μg/m 3 increase in concentration of PM 10 , SO 2 and NO 2 at lag 5 day were associated with an increase of 1.39%, 1.56%, and 1.18% respectively in cardiovascular disease emergency admissions. For lag 02, a 10 μg/m 3 increase in concentration of PM 10 , SO 2 and NO 2 were associated with 1.72%, 1.34%, and 2.57% increases respectively in respiratory disease emergency admissions. Conclusion This study further confirmed that short-term exposure to ambient air pollution was associated with increased risk of hospital emergency admissions in Beijing. [ABSTRACT FROM AUTHOR]

Severe typhoon Damrey moved across Hainan Island from 00:00 UTC 25 September to 00:00 UTC 27 September in 2005 and gave rise to a significant rain process during its 48-h passage. The precipitation intensity on the southern part of the island is stronger than that on the northern, showing obvious asymmetric distribution. Using Tropical Rainfall Measuring Mission (TRMM) data, the associated mesoscale characteristics of the precipitation were analyzed and the formation of asymmetric rainfall distribution was investigated in the context of a subsynoptic scale disturbance, vertical wind shear and orographic factors. The results are shown as follows. (1) The subsynoptic scale system provided favorable dynamic conditions to the genesis of mesoscale rain clusters and rainbands. (2) The southern Hainan Island was located to the left of the leeward direction of downshear all the time, being favorable to the development of convection and leading to the asymmetric rainfall distribution. (3) Mountain terrain in the southern Hainan Island stimulated the genesis, combination and development of convective cells, promoting the formation of mesoscale precipitation systems and ultimately resulting in rainfall increase in the southern island. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article on the weather temperature and air pollution interaction and its effect on hospital admissions due to respiratory system diseases in Western China.

To explore the influence characteristics of the interaction effects between meteorological factors on ozone(O 3 ) concentration in Chengdu, daily air pollutants and meteorological data from 2014 to 2019 were collected. Generalized additive models(GAMs) were adopted to explore the effects of different factors on O 3 concentration. The results showed that the relationship between O 3 and maximum temperature, sunshine hours, relative humidity, wind speed, precipitation, maximum mixed depth(MMD), and ventilation coefficient(VC) was non-linear. Specifically, the maximum temperature, sunshine hours, MMD, and relative humidity had a significant influence on O 3 concentration throughout the year. It is worth noting that the influence of relative humidity and precipitation on O 3 concentration during summer was more significant than that for the whole year. In the multi-meteorological factors GAMs of O 3 concentration, the meteorological factors mentioned above, except average wind, had significant impacts on O 3 concentration change. For the whole year, the judgment coefficient( R 2 ) was 0.849 and the variance explanation rate was 85.1%. The maximum temperature was the most important influencing factor on O 3 concentration throughout the year. During summer, corresponding R 2 was 0.811 and the explanation rate of variance was 81.3%; however, maximum temperature and MMD were the dominant meteorological factors. In the interaction GAMs, for the whole year, the interaction between maximum temperature and sunshine hours, relative humidity, and precipitation, and the interaction between sunshine hours and MMD had a significant impact on O 3 concentrations. The interaction between maximum temperature and sunshine hours played a leading role in changes of O 3 concentration. The high temperature+strong radiation+MMD(about 2000 m) +no precipitation were conducive to the formation of O 3 concentration, but in summer, only the maximum temperature, sunshine hours, and VC had the most significant effect on the O 3 concentration, and strong high temperatures+strong radiation+the little horizontal wind in summer were conducive to the formation of O 3 concentration near the surface. In summary, GAMs model can not only be used to identify the dominant influencing factors of O 3 pollution, but also quantitatively analyze the influence of single effects and interaction of influencing factors on O 3 concentration, which has great significance for the prevention and control of O 3 pollution.

Objective: To explore the health risks of the interactive effects between PM2.5 and ozone on cardiovascular mortality in Chengdu., Methods: Daily data on the mortality of cardiovascular diseases, including data for both men and women, during 2014-2016 were collected. The meteorological data, the daily average of particulate matter with aerodynamic diameter less than 2.5 micrometers (PM2.5), and the daily ozone 8 h maximum concentration (O 3 8-h max) in Chengdu of the same period were also collected. Generalized Additive Models (GAMs) were adopted to explore the respective adverse health effects of PM2.5 and O 3 8-h max and the synergistic effects between PM2.5 and O 3 8-h max on the mortality of cardiovascular diseases in the city., Results: The highest health risks of PM2.5 and O 3 8-h max for mortality of cardiovascular diseases were found to be the strongest for the cumulative effect of the lag of one day (lag01). For every 10 µg/m 3 increment in the mass concentration of PM2.5 (lag01), the associated increase in risks for total, male, and female cardiovascular mortalities was 0.35%, 0.26% and 0.38%, respectively. For every 10 µg/m 3 increment in the mass concentration of O 3 8-h max (lag01), the associated increase in risks for total, male, and female cardiovascular mortalities was 0.66%, 0.43%, and 1.05%, respectively. The total, male, and female cardiovascular mortalities all reached their maximum values when high concentration of PM2.5 coexisted with high concentrations of O 3 8-h max., Conclusion: There was a synergistic amplification effect between high concentrations of PM2.5 and high concentrations of O 3 8-h max on cardiovascular mortality., (Copyright© by Editorial Board of Journal of Sichuan University (Medical Sciences).)

Much of the current uncertainty in the quantitative assessment of the climate and environment change is due to our lack of knowledge of the aerosol, for which the large-scale sun hazemeter ground-based network directly provides basic data. The data also can revise the results of the satellite remote sensing. Depending on the stations of CERN, the standard network was first built in China. The accurate and reliable hazemeter (LEDs) was uniformly used in the network. The hazemeters were calibrated by Langley plot method and transfer calibration and were uniformly checked. The AODs, which were synchronously retrieved from hazemeters (RSD < 3%) and CEMIL (RSD < 5%), were coherent and comparable. The stability and reliability of the hazemeters and the network was approved.

Atmospheric aerosol optical depth (AOD(lamda=500 nm)), Angstrom turbidity coefficient (beta) and Angstrom wavelength exponent (alpha) are obtained using the CERN sun hazemeter network from Aug to Dec, 2004. The results are as follows: At the Tibetan Plateau, Haibei and Lhasa, the mean of AOD is 0.09, 0.12; the mean of beta is 0.05, 0.13; the mean of a is 1.09, 0.06, respectively. At the Northeast of China, Hailun and Sanjiang, the mean of AOD is 0.14, 0.15; the mean of beta is 0.04, 0.06; the mean of a is 2.32, 1.58, respectively. At the desert region of North China, e.g., Fukang, Shapotou and Eerduosi, the range of averaged AOD is from 0.17 to 0.32; the range of averaged beta is from 0.09 to 0.19; the range of averaged a is from 0.68.to 1.28. At the forest areas, e.g. Changbai Mountain, Beijing forest and Xishuangbanna, the range of averaged AOD is from 0.19 to 0.42; the range of averaged beta is from 0.12 to 0.19; the range of averaged a is from 1.11 to 1.25. At agriculture areas, e.g. Shenyang, Fengqiu, Taoyuan and Yanting, the range of averaged AOD is from 0.34 to 0.68; the range of averaged beta is from 0.18 to 0.38; the range of averaged a is from 0.97 to 1.39. At the littoral areas and the lake of East China, e.g. Jiaozhou Bay, Shanghai City and Tai Lake, the range of averaged AOD is from 0.49 to 0.68; the range of averaged beta is from 0.21 to 0.29; the range of averaged a is from 1.24 to 1.37. At the inland cities, Beijing City and Lanzhou City, the mean of AOD is 0.47, 0.81; the mean of beta is 0.20, 0.45; the mean of a is 1.66, 0.89, respectively. The variations of aerosol properties at nineteen stations are explained in the paper.